For many years, information technology (IT) organizations (the “providers”) have offered IT management services and computing resources to other business entities (the “customers”). In a “traditional” service model, the customers share a provider's management services, but each customer purchases or leases specific resources for the customer's exclusive benefit. The customer may purchase or lease the resources directly from the provider or from a third party. Regardless of their origins, though, such a purchase or lease may require extensive, time-consuming negotiations based upon the customer's anticipated requirements. If the customer's requirements are less than anticipated, then the customer effectively has wasted resources. If, however, the customer's requirements are greater than anticipated, then the customer may have to enter into additional time-consuming negotiations for the necessary resources.
Customers of “on-demand” services, on the other hand, share the provider's management services and computing resources (to the system and subsystem level), including persistent memory (“storage”), volatile memory (“memory”), and processors, as depicted in FIG. 1. As FIG. 1 also illustrates, another characteristic of the on-demand model is multiple customers sharing the same subsystem within the same computing resource, such as a logical partition (LPAR). In FIG. 1, for example, customer 3 and customer 4 could each run separate instances of operating system 3, such as Z/LINUX, on a single z/VM LPAR. Multiple external customers sharing singular hardware requires that performance tuning not only be applicable to the workload, but to the entire customer and the other customers sharing the hardware.
Generally, the on-demand provider delivers services based upon a contract that allows a variance of utilization. The provider delivers the requested services without regard to the physical resources used to provide those services. The customer does not purchase or lease the physical resources; instead, the provider retains the discretion to allocate the resources to logical partitions as needed to meet its service obligations. Typically, the provider establishes threshold levels of service that guide dynamic allocation of resources. Although on-demand customers may share a provider's services and computing resources, the provider generally must segregate and protect each customer's data.
While the on-demand service model addresses many of the problems of the traditional model, including wasted resources and time-consuming negotiations, it presents some unique problems of its own. Specifically, the on-demand provider must ensure that dynamic resource allocation does not interrupt any customer's service. The provider also must ensure that dynamic resource allocation for one customer does not negatively impact service performance or security for any other customer that shares the resources. Because the concept of dynamic resource allocation is foreign to the traditional service model, the traditional service management processes do not support these unique needs of the on-demand service model.
Therefore, one skilled in the art should appreciate the need for a detailed performance management method that allocates resources, at the system and subsystem level, in a dynamically shared computing environment, and ensures that the demands of one customer's applications are not affected by the allocation and utilization of the other customers who share these IT resources.